It is exceedingly challenging to discern one infosecurity capacity from another in the cybersecurity industry because of the abundance of confusing buzzwords and competing acronyms.

You’re not alone if your attempts to comprehend the cybersecurity components you need to pay attention to have left you disappointed.

Let’s get right to the point and distinguish fact from fiction in reference to the most popular buzzwords in cybersecurity.


Artificial Intelligence, Machine learning, and User and Entity Behavior Analytics


That’s true. These major three should all be considered a single entity. Currently, the terms artificial intelligence (AI) and machine learning (ML) are used interchangeably and are both highly important ideas. Although they are connected, they aren’t nearly the same thing. While machine learning (ML) is an application of AI based on the notion that computers should be able to learn on their own from the data presented to them, artificial intelligence is the more general concept of machines being able to carry out tasks in a way that people would deem “clever.”


Machine learning is used by an actionable security intelligence platform to comprehend and forecast typical system behavior and event occurrences within a business. Machine learning is used for User and Entity Activity Analytics in the context of cybersecurity (UEBA).


Machine learning is a tool that UEBA capabilities employ to learn how users (people) and entities (machines) normally act in a given environment. It searches for dangerous, aberrant conduct that differs from typical user behavior and issues alerts in response to anything that might suggest a threat.


Examples of this type of behavior include users using a system outside of their regular behavior patterns, such as at odd hours or locations. An illustration of entity behavior would be the use of a compromised computer as a point of access to try to log into various other servers and assets.


First, event and log data must be gathered and stored within the SIEM (Security Information and Event Management) technology, which is ultimately an actionable security intelligence platform, before any analysis, correlation, or reporting can be done.


Security Information and Event Management (SIEM)


You might be thinking, “But wait, didn’t some seller warn me ‘SIEM is dead’?” Nothing is more false than it is. The truth is that the first-generation SIEM platform has expired. There was the one that was nearly impossible to deploy, gathered enormous volumes of logs, and produced an unmanageable number of false positive warnings that an analyst could safely disregard. Of course that SIEM is dead and ought to be.


That assertion is false since the understanding and expectations of a SIEM today are very different. The capability provided by point solutions like as endpoint threat detection and response (EDR), intrusion detection system (IDS), user and entity behavior analysis (UEBA), threat intelligence feeds, and others will be incorporated into any SIEM solution worth its salt.


The best SIEM solutions available today should also include reasonable pricing structures, deployment choices, and managed services.


Security Orchestration and Automated Response (SOAR)


By recognizing and alerting to real threats while reducing false positives, machine learning capabilities enable a platform to more successfully find the aforementioned “needle in a haystack.”


Security analysts must still respond to these instances, though.


To improve remedial consistency, speed up response times, and boost SOC output, EventTracker adds SOAR capabilities. For instance, a company’s IT management platform enables the quick termination of unknown activities, monitoring for the spread of suspected malware, and recording incidents for incident reports (Security Orchestration).


In this situation, EventTracker not only “says something,” but also “does something” when it senses a threat (Automated Response).


Intelligence-Driven Security Operations Center (iSOC)


Technology is merely one component of the puzzle. Many firms don’t have the personnel or funding to fully use their threat lifecycle management investment.


A team of security experts equipped with both global and local threat intelligence makes up a comprehensive managed solution. They are stacked on top of a SIEM platform to carry out round-the-clock monitoring, analysis, and incident response.


Essentially, this is SOC-as-a-Service. The I in iSOC denotes the presence of a threat research lab, which in some situations functions as a separate entity.


An iSOC typically consists of:


  • SOC Analysts: Tier 1 and 2 security analysts monitoring events, delivering critical observations reports (COR), and responding to early warning health alarms
  • CSIRT: Tier 3 incident response analysts reviewing the COR and managing priority 1 incidents
  • Threat Research Lab: Analysts focused on collating indicators of compromise (IOC) from multiple sources
  • Platform Specialists: SIEM administrators who collaborate with engineering on product enhancements and fixes as well as perform routine tuning to optimize the installation


The iSOC oversees systems administration and tuning, creates reaction playbooks, and conducts regular executive summaries utilizing key observation reports thanks to CYB3R-X’s Managed Threat Protection solution (CORs).


For many enterprises, this co-managed SIEM solution is a significantly more affordable way to achieve security and compliance goals.


There you have it. Although they are frequently misunderstood or abused, terms like artificial intelligence (AI), machine learning (ML), user and entity behavior analytics (UEBA), security orchestration and automated response (SOAR), and intelligence-driven security operations center (iSOC) actually convey useful cybersecurity concepts and capabilities when used correctly.


Your particular situation will determine the best method to apply these concepts to your firm. To learn more about the cybersecurity solution that is best for you, talk to a CYB3R-X expert today or email us at for a demo.